AMS 103rd Annual Meeting: "Data: Driving Science. Informing Decisions. Enriching Humanity."

As an FYI, the theme of the upcoming 103rd AMS Annual Meeting has been released here. It should resonate very strongly with the community here. Copy/paste the “Motivation” below the fold but the whole statement is worth a read.

The meeting is January 8-12, 2023 in Denver, CO. If anyone is interested in proposing/chairing sessions related to work they’re doing in regard to open data/science please do so! The deadline for Session Topic Proposals is April 7; proposals can be submitted through the User Portal.

Motivation for the theme on Data
Environmental Earth and space system data has one of the largest digital footprints and is a central component of scientific inquiry, but we have not yet collectively solved the problem of data access, discovery, and service. This theme will be the catalyst for a year-long inclusive and collaborative discourse on the challenges posed by the data deluge with a focus on how to stage environmental data to make it efficiently useful and accessible for the plethora of applications important to driving science, informing decisions, and enriching humanity within our community and beyond.

Data is the engine of hypothesis-driven science and the fuel for inductive, empirical investigation. In recent years, atmospheric, oceanic, climate, and hydrological data have come to be as much of an asset as any natural resource. Databases and their derivatives have become increasingly valuable commodities. On the other hand, the paucity of data in regions (e.g., parts of the ocean, polar regions, and some rural areas) impairs decision-making and could affect prediction scenarios for climate change and other global environmental changes. As the value proposition of data has grown, nations of the world are revisiting arrangements to share data, improve data collection, drive research and innovation, stimulate two-way transfer of research [R] and operations [O] (R2O2R), support education and training, and economic growth. Big Data is revolutionizing knowledge production by enabling novel, highly efficient ways to conduct research. The field of data science is creating new techniques for extrapolating knowledge and emergent discovery from data. The Open Data movement, emerging from policy trends such as “Open Government and Open Science,” encourages sharing data via digital infrastructures, which, in turn can serve as scaffolding for the development of artificial intelligence (AI) and machine learning (ML), and an incentive for more efficient processing, reuse, and knowledge creation.

The WWC research enterprise along with private and government sectors will lead the way in finding the acumen, resources, and technological prowess to effectively harness the data revolution to advance their imperatives, exploit emergent technologies, and pursue frontiers.

Still, as a community we have the shared obligation to ensure that the next generation workforce is prepared for a world where data profoundly influences every facet of the enterprise. Academic curricula must evolve to accommodate a new balance between foundational underpinnings in science and mathematics, the breadth of technical skills, cross-disciplinarity and cross-cultural competencies, and the wherewithal to use data responsibly for the common good. Our imperative must be to ensure that data in all its forms, and the actions taken based on this data, are free of biases and fully accessible.